Is stochastic volatility more flexible than garch?

This paper compares the ability of GARCH and ARSV models to represent adequately the main empirical properties usually observed in high frequency financial time series: high kurtosis, small first order autocorrelation of squared observations and slow decay towards zero of the autocorrelation coefficients of squared observations. We show that the ARSV(1) model is more flexible than the GARCH(1,1) model in the sense that it is able to generate series with higher kurtosis and smaller first order autocorrelation of squares for a wider variety of parameter specifications. Our results may help to clarify some puzzles raised in the empirical analysis of real financial time series

Detecting level shifts in the presence of conditional heteroscedasticity.

The objective of this paper is to analyze the finite sample performance of two variants of the likelihood ratio test for detecting a level shift in uncorrelated conditionally heteroscedastic time series. We show that the behavior of the likelihood ratio test is not appropriate in this context whereas if the test statistic is appropriately standardized, it works better. We also compare two alternative procedures for testing for several level shifts. The results are illustrated by analyzing daily returns of exchange rates

DETECTING LEVEL SHIFTS IN THE PRESENCE OF CONDITIONAL HETEROSCEDASTICITY

The objective of this paper is to analyze the finite sample performance of two variants of the likelihood ratio test for detecting a level shift in uncorrelated conditionally heteroscedastic time series. We show that the behavior of the likelihood ratio test is not appropriate in this context whereas if the test statistic is appropriately standardized, it works better. We also compare two alternative procedures for testing for several level shifts. The results are illustrated by analyzing daily returns of exchange rates.EGARCH, GARCH, Likelihood Ratio, Stochastic Volatility.

Estimating and Forecasting GARCH Volatility in the Presence of Outiers

The main goal when fitting GARCH models to conditionally heteroscedastic time series is to estimate the underlying volatilities. It is well known that outliers affect the estimation of the GARCH parameters. However, little is known about their effects when estimating volatilities. In this paper, we show that when estimating the volatility by using Maximum Likelihood estimates of the parameters, the biases incurred can be very large even if estimated parameters have small biases. Consequently, we propose to use robust procedures. In particular, a simple robust estimator of the parameters is proposed and shown that its properties are comparable with other more complicated ones available in the literature. The properties of the estimated and predicted volatilities obtained by using robust filters based on robust parameter estimates are analyzed. All the results are illustrated using daily S&P500 and IBEX35 returns.Heteroscedasticity, M-estimator, QML estimator, Robustness, Financial Markets

SPURIOUS AND HIDDEN VOLATILITY

This paper analyzes the effects caused by outliers on the identification and estimation of GARCH models. We show that outliers can lead to detect spurious conditional heteroscedasticity and can also hide genuine ARCH effects. First, we derive the asymptotic biases caused by outliers on the sample autocorrelations of squared observations and their effects on some homoscedasticity tests. Then, we obtain the asymptotic biases of the OLS estimates of ARCH(p) models and analyze their finite sample behaviour by means of extensive Monte Carlo experiments. The finite sample results are extended to GLS and ML estimates ARCH(p) and GARCH(1,1) models.GARCH, Outliers, Heteroscedasticity

DETECTING LEVEL SHIFTS IN THE PRESENCE OF CONDITIONAL HETEROSCEDASTICITY.

The objective of this paper is to analyze the finite sample performance of two variants of the likelihood ratio test for detecting a level shift in uncorrelated conditionally heteroscedastic time series. We show that the behavior of the likelihood ratio test is not appropriate in this context whereas if the test statistic is appropriately standardized, it works better. We also compare two alternative procedures for testing for several level shifts. The results are illustrated by analyzing daily returns of exchange rates.

Stock Market Regulations and Internacional Financial Integration: the case of Spain.

International financial integration effects on the Spanish stock market are studied, both for the conditional mean and conditional variance. New institutional regulations in Spain are taken into account and their efficiency consequences are addressed. Results suggest an increasing international integration but nontrivial opportunities for financial diversification may still be relevant.Financial integration; Market reforms; Stochastic volatility;

Outliers and conditional autoregressive heteroscedasticity in time series

This paper reviews the literature on GARCH-type models proposed to represent the dynamic evolution of conditional variances. Effects of level outliers on the diagnostic and estimation of GARCH models are also studied. Both outliers and conditional heteroscedasticity can generate time series with excess kurtosis and autocorrelated squared observations. Consequently, both phenomena can be confused. However, since outliers are generated by unexpected events and the conditional variances are predictable, it is important to identify which one is producing the observed features in the data. We compare two alternative procedures for dealing with the simultaneous presence of outliers and conditional heteroscedasticity in time series. The first one is to clean the series of outliers before fitting a GARCH model. The second is to estimate first the GARCH model and then to clean of outliers by using the residuals adjusted by its conditional variance. It is shown that both approaches may result in different estimated conditional variances

Stock market regulations and international financial integration: the case of Spain

International financial integration effects on Spanish stock market are studied, both for the conditional mean and conditional variance. New institutional regulations in Spain are taken into account and its efficiency consequences are addressed. Results suggest an increasing international integration but nontrivial opportunities for financial diversification may still be relevant

Stock Market Regulations and Internacional Financial Integration: the case of Spain

International financial integration effects on the Spanish stock market are studied, both for the conditional mean and conditional variance. New institutional regulations in Spain are taken into account and their efficiency consequences are addressed. Results suggest an increasing international integration but nontrivial opportunities for financial diversification may still be relevant.Publicad